High Efficiency Video Coding Research Articles

4D Epanechnikov Mixture Regression in LF Image Compression

With the emergence of light field imaging in recent years, the compression of its elementary image array (EIA) has become a significant problem. Our coding framework includes modeling and reconstruction. For the modeling, the covariance-matrix form of the 4-D Epanechnikov kernel (4-D EK) and its correlated statistics were deduced to obtain the 4-D Epanechnikov mixture models (4-D EMMs). A 4-D Epanechnikov mixture regression (4-D EMR) was proposed based on this 4-D EK, and a 4-D adaptive model selection (4-D AMLS) algorithm was designed to realize the optimal modeling for a pseudo video sequence (PVS) of the extracted key-EIA. A linear function based reconstruction (LFBR) was proposed based on the correlation between adjacent elementary images (EIs). The decoded images realized a clear outline reconstruction and superior coding efficiency compared to high-efficiency video coding (HEVC) and JPEG 2000 below approximately 0.05 bpp. This work realized an unprecedented theoretical application by (1) proposing the 4-D Epanechnikov kernel theory, (2) exploiting the 4-D Epanechnikov mixture regression and its application in the modeling of the pseudo video sequence of light field images, (3) using 4-D adaptive model selection for the optimal number of models, and (4) employing a linear function-based reconstruction according to the content similarity.

Object Tracking Based Surgical Incision Region Encoding using Scalable High Efficiency Video Coding for Surgical Telementoring Applications

Object Tracking Based Surgical Incision Region Encoding using Scalable High Efficiency Video Coding for Surgical Telementoring Applications

Editorial Real-Time Implementation of VVC Standard for Consumer Electronic Devices

We are pleased to present this Special Issue on this timely and important topic. The next generation ISO/IEC MPEG and ITU-T VCEG video coding standard called versatile video coding (VVC) was released in July 2020 <xref ref-type="bibr" rid="ref1">[1]</xref>, <xref ref-type="bibr" rid="ref2">[2]</xref>. Gls vvc includes some coding tools enabling an important coding gains estimated to 35&#x0025; of bit-rate reductions for the same quality in terms of peak signal to noise ration (PSNR) compared with high efficiency video coding (HEVC) in random access (RA) coding configurations. For all intra (AI) configuration the improvement is a bit lower and estimated in a 25&#x0025;. Moreover, subjective comparison recently conducted between HEVC and the VVC reference software, has shown that this gain is even higher reaching up to 50&#x0025; of bit-rate reduction for the same perceived quality <xref ref-type="bibr" rid="ref3">[3]</xref> - <xref ref-type="bibr" rid="ref4">[4]</xref>. Unfortunately the coding gain is associated to an increase in the algorithm complexity at both encoder and decoder sides. The VVC encoder is estimated to be <inline-formula> <tex-math notation="LaTeX">$8\times $ </tex-math></inline-formula> more complex than HEVC in RA configuration and <inline-formula> <tex-math notation="LaTeX">$25\times $ </tex-math></inline-formula>. The complexity of the VVC decoder is doubled compared to HEVC. Therefore, complexity reduction and optimization of VVC is critical to design of software and hardware real time VVC codecs for successful deployment on video consumer devices including among others TVs, mobile phones and tablets.

VVC Search Space Analysis Including an Open, Optimized Implementation

Versatile Video Coding (VVC) is a new video coding standard finalized in July 2020. During the standard development much attention was paid to keeping the decoding complexity increase as small as possible, with more permissive approach being taken with regard to the encoding. The VVC reference software VTM in random access configuration requires around double the time to decode and <inline-formula> <tex-math notation="LaTeX">$8\times $ </tex-math></inline-formula> the time to encode a video, compared to High Efficiency Video Coding (HEVC) reference software HM. With this runtime increase, an objective bitrate reduction of around 40&#x0025; is achieved. In this paper we analyze the encoding complexity increase of VVC over HEVC. We abstract the implementation-based aspects, including low-level software optimizations and introduce an empirical measure to quantify the extent of encoder search space given a specific search algorithm. Based on the measure, we compare the search space of HM and VTM, but also of the open and optimized VVC encoder implementation VVenC, showing the potential for search space reduction and its impact on compression performance. Overall, it can be seen that while VVC&#x2019;s search space is quite large in VTM, it can be efficiently limited either by including early termination strategies or by disabling VVC coding tools.

Toward Generalized Psychovisual Preprocessing For Video Encoding

Deep perceptual preprocessing has recently emerged as a new way to enable further bitrate savings across several generations of video encoders without breaking standards or requiring any changes in client devices. In this article, we lay the foundation for a generalized psychovisual preprocessing framework for video encoding and describe one of its promising instantiations that is practically deployable for video-on-demand, live, gaming, and user-generated content (UGC). Results using state-of-the-art advanced video coding (AVC), high efficiency video coding (HEVC), and versatile video coding (VVC) encoders show that average bitrate [Bjontegaard delta-rate (BD-rate)] gains of 11%–17% are obtained over three state-of-the-art reference-based quality metrics [Netflix video multi-method assessment fusion (VMAF), structural similarity index (SSIM), and Apple advanced video quality tool (AVQT)], as well as the recently proposed nonreference International Telecommunication Union-Telecommunication?(ITU-T) P.1204 metric. The proposed framework on CPU is shown to be twice faster than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times 264$ </tex-math></inline-formula> medium-preset encoding. On GPU hardware, our approach achieves 714 frames/sec for 1080p video (below 2 ms/frame), thereby enabling its use in very-low-latency live video or game streaming applications.

Low-Complexity Intra Coding in Versatile Video Coding

Versatile Video Coding (VVC) was finalized in 2020 and offered promising coding efficiency with a bitrate reduction of about 50&#x0025; for same video quality as High Efficiency Video Coding. However, its high encoding complexity is a heavy burden on real-time applications. In particular, the very high complexity in intra coding can be a big barrier into market entry. This paper presents an efficient low-complexity intra coding scheme, which employs downsampling and upsampling processes. The downsampling is simply performed by reducing the resolution of an original video in both horizontal and vertical directions. In the upsampling, convolutional neural network based super-resolution is used to increase the resolution of the reconstructed video. In addition, this paper thoroughly analyzes the performance and complexity of all intra coding tools in VVC. Experimental results demonstrate that the significantly high reduction of the encoding complexity can be achieved with acceptable video quality.

Adaptive Loop Filter Hardware Design for 4K ASIC VVC Decoders

Versatile video coding (VVC) is the next generation video coding standard released in July 2020. VVC introduces new coding tools enhancing the coding efficiency compared to its predecessor high efficiency video coding (HEVC). These new tools have a significant impact on the VVC software decoder with a complexity estimated to two times HEVC decoder complexity. In particular, the adaptive loop filter (ALF) introduced in VVC as an in-loop filter increases both the decoding complexity and memory usage. These concerns need to be carefully addressed regarding the design of an efficient hardware implementation of a VVC decoder. In this paper, we present an efficient hardware implementation of the ALF tool for VVC decoder. The proposed solution establishes a novel scanning order between Luma and Chroma components that reduces significantly the ALF memory. The design takes advantage of all ALF features and establishes an unified hardware module for all ALF filters. The design uses 26 regular multipliers in a pipelined architecture with a fixed throughput of 2 pixels/cycle and fixed system latency regardless of the selected filter. This design operates at 600 MHz frequency enabling to decode on ASIC platform a 4K video at 30 frames per second in 4:2:2 chroma sub-sampling format.

From HEVC to VVC: The First Development Steps of a Practical Intra Video Encoder

Versatile Video Coding (VVC/H.266) is an emerging successor to the widespread High Efficiency Video Coding (HEVC/H.265) and is shown to double the coding efficiency for the same subjective visual quality. Nevertheless, VVC still adopts the similar hybrid video coding scheme as HEVC and thereby sets the scene for reusing many HEVC coding tools and techniques as is or with minor modifications. This paper explores the feasibility of developing a practical software VVC intra encoder from our open-source Kvazaar HEVC encoder. The outcome of this work is called uvg266 VVC intra encoder that is distributed under the same permissive 3-clause BSD license as Kvazaar. uvg266 inherits the optimized coding flow of Kvazaar and all upgradable Kvazaar intra coding tools, but it also introduces basic VVC intra coding tools not available in HEVC. To the best of our knowledge, this is the first work to describe the implementation details of upgrading an HEVC encoder to a VVC encoder. The rapid development time with promising coding performance make our proposal a viable approach over the encoder development from scratch.

Interlayer Restoration Deep Neural Network for Scalable High Efficiency Video Coding

This paper applies an interlayer restoration deep neural network (IRDNN) for scalable high efficiency video coding (SHVC) to improve visual quality and coding efficiency. It is the first time to combine deep neural network (DNN) and SHVC. Considering the coding architecture of SHVC, we elaborate a multi-frame and multi-layer neural network to restore the interlayer of SHVC by utilizing both the adjacent reconstructed frames of the base layer (BL) and enhancement layer (EL). Moreover, we analyze the temporal motion relationship of frames in one layer and the compression degradation relationship of frames between different layers, and propose the synergistic mechanism of motion restoration and compression restoration in our IRDNN. The network can generate an interlayer with higher quality serving for the EL coding and thus enhance the coding efficiency. A large-scale and various-quality-degradation dataset is self-made for the task of interlayer restoration of SHVC. The experimental results show that with our implementation on SHVC, the EL Bj<inline-formula> <tex-math notation="LaTeX">$\phi $ </tex-math></inline-formula>ntegaard delta bit-rate (BD-BR) reduction is 9.291&#x0025; and 6.007&#x0025; in signal-to-noise ratio scalability and spatial scalability, respectively. The code is available at <i><uri>https://github.com/icecherylXuli/IRDNN</uri></i>.

Bagged Tree and ResNet-Based Joint End-to-End Fast CTU Partition Decision Algorithm for Video Intra Coding

Video coding standards, such as high-efficiency video coding (HEVC), versatile video coding (VVC), and AOMedia video 2 (AV2), achieve an optimal encoding performance by traversing all possible combinations of coding unit (CU) partition and selecting the combination with the minimum coding cost. It is still necessary to further reduce the encoding time of HEVC, because HEVC is one of the most widely used coding standards. In HEVC, the process of searching for the best performance is the source of most of the encoding complexity. To reduce the complexity of the coding block partition in HEVC, a new end-to-end fast algorithm is presented to aid the partition structure decisions of the coding tree unit (CTU) in intra coding. In the proposed method, the partition structure decision problem of a CTU is solved by a novel two-stage strategy. In the first stage, a bagged tree model is employed to predict the splitting of a CTU. In the second stage, the partition problem of a 32 × 32-sized CU is modeled as a 17-output classification task for the first time, so that it can be solved by a single prediction. To achieve a high prediction accuracy, a residual network (ResNet) with 34 layers is employed. Jointly using bagged tree and ResNet, the proposed fast CTU partition algorithm is able to generate the partition quad-tree structure of a CTU through an end-to-end prediction process, which abandons the traditional scheme of making multiple decisions at various depth levels. In addition, several datasets are used in this paper to lay the foundation for high prediction accuracy. Compared with the original HM16.7 encoder, the experimental results show that the proposed algorithm can reduce the encoding time by 60.29% on average, while the Bjøntegaard delta rate (BD-rate) loss is as low as 2.03%, which outperforms the results of most of the state-of-the-art approaches in the field of fast intra CU partition.

BVI-CC: A Dataset for Research on Video Compression and Quality Assessment

The video technology scenery has been very vivid over the past years, with novel video coding technologies introduced that promise improved compression performance over state-of-the-art technologies. Despite the fact that a lot of video datasets are available, representative content of the wide parameter space along with subjective evaluations of variations of encoded content from an unpartial end is required. In response to this requirement, this paper features a dataset, the BVI-CC. Three video codecs were deployed to create the variations of the encoded sequences: High Efficiency Video Coding Test Model (HM), AOMedia Video 1 (AV1), and Versatile Video Coding Test Model (VTM). Nine source video sequences were carefully selected to offer both diversity and representativeness in the spatio-temporal domain. Different spatial resolution versions of the sequences were created and encoded by all three codecs at pre-defined target bit rates. The compression efficiency of the codecs was evaluated with commonly used objective quality metrics, and the subjective quality of their reconstructed content was also evaluated through psychophysical experiments. Additionally, an adaptive bit rate (convex hull rate-distortion optimization across spatial resolutions) test case was assessed using both objective and subjective evaluations. Finally, the computational complexities of the tested codecs were examined. All data have been made publicly available as part of the dataset, which can be used for coding performance evaluation and video quality metric development.

A Fast CABAC Hardware Design for Accelerating the Rate Estimation in HEVC

The latest High Efficiency Video Coding standard achieves twice the coding efficiency of the H264 standard through a complex rate-distortion optimization (RDO). The coded bit-streams are produced with context adaptive binary arithmetic coding (CABAC). CABAC itself is a very time-consuming process that includes binarization, context modeling, interval subdivision, renormalization, outstanding bit handling, and context updating. The aim of this research is to speed up the CABAC process through several simplifications. First, we approximate three parts of the CABAC, i.e., interval subdivision, renormalization, and outstanding bit handling, with a piecewise-linear function that is very friendly to hardware implementation. In order to achieve better hardware parallelism, we also improve the coding process at the sub-block level. The context of syntax elements in a sub-block is redistributed to skip the complex calculation of context indexing. We perform context updating at the granularity of sub-blocks so that the data dependency of the context updating is removed completely, and the original serial encoding process is changed to a parallel encoding process. At the same time, we make another simplification for the context modeling of <i>cu&#x005F;skip&#x005F;flag</i>. Based on these simplifications, we build a parallel hardware architecture for the rate estimation of the RDO process. This architecture completes the bit estimation of a <inline-formula> <tex-math notation="LaTeX">$32\times 32$ </tex-math></inline-formula> coding tree unit (CTU) in 220.8 nano-seconds, whereas the Bj&#x00F8;ntegaard Delta rate increases by only 2.225&#x0025;. We believe that the proposed architecture can meet the requirements of 8K&#x0040;120 fps ultra-high-definition videos. This is the first study to simplify the hardware design of rate estimation by changing the context allocation and updating rules.

Activity-Based Block Partitioning Decision Method for Versatile Video Coding

Versatile Video Coding (VVC), the latest international video coding standard, has more than twice the compression performance of High-Efficiency Video Coding (HEVC) through adopting various coding techniques. The multi-type tree (MTT) block structure offers more advanced flexible block partitioning by allowing the binary tree (BT) and ternary tree (TT) structures, as well as the quadtree (QT) structure. Because VVC selects the optimal block partition by performing encoding on all possible CU partitions, the encoding complexity increases enormously. In this paper, we observe the relationship between block partitions and activity that indicates block texture complexity. Based on experimental observations, we propose an activity-based fast block partitioning decision method to reduce the encoding complexity. The proposed method uses only information of the current block without using the information of neighboring or upper blocks, and also minimizes the dependency on QP. For these reasons, the proposed algorithm is simple and parallelizable. In addition, by utilizing the gradient calculation used in VVC’s ALF, a VVC-friendly fast algorithm was designed. The proposed method consists of two-step decision-making processes. The first step terminates the block partitioning early based on observed posterior probability through the relationship between the block size and activity per sample. Next, the sub-activities of the current block are used to determine the type and direction of partitioning. The experimental results show that in the all-intra configuration, the proposed method can reduce the encoding time of the VVC test model (VTM) by up to 45.15% with 2.80% BD-rate loss.

A Crypto-Steganography Approach for Hiding Ransomware within HEVC Streams in Android IoT Devices.

Steganography is a vital security approach that hides any secret content within ordinary data, such as multimedia. This hiding aims to achieve the confidentiality of the IoT secret data; whether it is benign or malicious (e.g., ransomware) and for defensive or offensive purposes. This paper introduces a hybrid crypto-steganography approach for ransomware hiding within high-resolution video frames. This proposed approach is based on hybridizing an AES (advanced encryption standard) algorithm and LSB (least significant bit) steganography process. Initially, AES encrypts the secret Android ransomware data, and then LSB embeds it based on random selection criteria for the cover video pixels. This research examined broad objective and subjective quality assessment metrics to evaluate the performance of the proposed hybrid approach. We used different sizes of ransomware samples and different resolutions of HEVC (high-efficiency video coding) frames to conduct simulation experiments and comparison studies. The assessment results prove the superior efficiency of the introduced hybrid crypto-steganography approach compared to other existing steganography approaches in terms of (a) achieving the integrity of the secret ransomware data, (b) ensuring higher imperceptibility of stego video frames, (3) introducing a multi-level security approach using the AES encryption in addition to the LSB steganography, (4) performing randomness embedding based on RPS (random pixel selection) for concealing secret ransomware bits, (5) succeeding in fully extracting the ransomware data at the receiver side, (6) obtaining strong subjective and objective qualities for all tested evaluation metrics, (7) embedding different sizes of secret data at the same time within the video frame, and finally (8) passing the security scanning tests of 70 antivirus engines without detecting the existence of the embedded ransomware.

RDNet: Rate–Distortion-Based Coding Unit Partition Network for Intra-Prediction

High efficiency video coding (HEVC) has been finalized as the most widely utilized video coding standard, jointly developed by ITU-T, VCEG, and MPEG. In HEVC, the quad-tree structure of the coding unit partition is one of the most substantial modules and provides significant coding gains following huge coding time. In this paper, a rate–distortion-based coding unit partition network (RDNet) is proposed to make partition decisions based on the statistical features. RDNet is composed of a prediction sub-network and a target sub-network, where the prediction sub-network is used to predict the CU partition modes of the intra-prediction and the target sub-network is designed to optimize the network parameters by evaluating the rate–distortion cost, respectively. To balance the prediction accuracy and the rate–distortion loss, a parameter-exchanging strategy is applied to control the parameters’ sharing between two networks. Experimental results prove that our model can reduce the encoding time of HEVC by 55.83~71.72% with an efficient BD-BR of 2.876~3.347%, and the ablation study evaluates the ability of our strategy on balancing the trade-off between coding accuracy and inference speed.

Error Performance Analysis of Wireless Video Communication Systems Employing Multi-level MPSK Modulation and MIMO Technologies

Real-time communications of high definition video with the available limited channel bandwidth is a fundamental requirement for modern mobile and wireless networks such as Wi-Fi, WiMax, 3G, LTE and the emerging 5G. To fulfill this requirement, H.264/AVC and High Efficiency Video Coding (HEVC) or H.265 standards have been implemented to achieve high error performance over wireless channels and large compression efficiency thereby optimizing channel bandwidth. The problem of establishing and maintaining reliable communication paths among mobile users employing multiclass bitstreams to achieve high spatial diversity and coding gains is a big challenge for researchers. In practice, multimedia standards employ data partitioning where different levels of importance are assigned to the multimedia content. The problem of transmission of coded HEVC data over wireless channels employing MIMO technologies to maximize high spatial diversity and coding gains has not been explicitly explored in existing research works. Moreover, to meet the demand of 5G networks in providing ultra-reliable low latency communications it is required to study fully the performance of multimedia data over wireless channels. To this end we propose, in this paper, to study and analyze the performance of coded MIMO systems employing a triple-class bitstreams source namely a high priority, medium priority and low priority class. The objective of our study is to promote Unequal Error Protection (UEP) as well as spatial diversity of the coded bitstreams without sacrificing the channel bandwidth and increasing the computational complexity. Space-Time Block Codes with Orthogonal properties and Hierarchical or Multi-level 8PSK modulation are considered in our analysis and the adopted approach will be shown, through numerical evaluation and simulations, that excellent UEP capabilities as well as high spatial diversity gains can be achieved. New Bit Error Rate (BER) expressions in closed form are derived for independent and identically distributed Rayleigh channel in the presence of Additive White Gaussian Noise (AWGN). Single and multiple fading channel reception systems with Maximum Ratio Combining (MRC) are considered. The simulations of our proposed UEP transmission model are designed and implemented in Matlab Simulink® R2017. It is shown that the most important priority data gives a coding gain of around 11 dB over the less important one at a BER of 10--6 for an 8-diversity order Orthogonal Space-Time Block Code (OSTBC) employing Hierarchical 8PSK modulation. This work can be extended to evaluate the error probability of multiuser coded systems for 4G and 5G networks.

Methods to develop high throughput hardware architectures for HEVC Deblocking Filter using mixed pipelined-block processing techniques

This paper presents four highly efficient hardware architectures for Deblocking Filter (DBF) which can be used in High-Efficiency Video Coding (HEVC) encoder or decoder. Mixed pipelined and block processing techniques are used in these architectures to achieve high throughput while consuming minimum possible area. In these proposed architectures, the coding tree unit with 64 × 64 blocks of pixels in a frame are processed in the form of 32 × 32 blocks of pixels. Once the deblocking filtering process completes, these pixels will be stored in block memory via output buffer. Experimental results on Application Specific Integrated Circuit (ASIC) and Field Programmable Gate Array (FPGA) platforms demonstrate that the proposed hardware architecture has a throughput improvement of 69% to 83% at the expense of slightly increased gate count compared to the previously known architectures of DBF. With 180 nm technology library, the fastest architecture out of the four achieves a throughput of 162 FPS (Frames per second) at an operating frequency of 250 MHz.

High-Level Synthesis Implementation of an Embedded Real-Time HEVC Intra Encoder on FPGA for Media Applications

High Efficiency Video Coding (HEVC) is the key enabling technology for numerous modern media applications. Overcoming its computational complexity and customizing its rich features for real-time HEVC encoder implementations, calls for automated design methodologies. This article introduces the first complete High-Level Synthesis (HLS) implementation for HEVC intra encoder on FPGA. The C source code of our open-source Kvazaar HEVC encoder is used as a design entry point for HLS that is applied throughout the whole encoder design process, from data-intensive coding tools like intra prediction and discrete transforms to more control-oriented tools such as context-adaptive binary arithmetic coding (CABAC). Our prototype is run on Nokia AirFrame Cloud Server equipped with 2.4 GHz dual 14-core Intel Xeon processors and two Intel Arria 10 PCIe FPGA accelerator cards with 40 Gigabit Ethernet. This proof-of-concept system is designed for hardware-accelerated HEVC encoding and it achieves real-time 4K coding speed up to 120 fps. The coding performance can be easily scaled up by adding practically any number of network-connected FPGA cards to the system. These results indicate that our HLS proposal not only boosts development time, but also provides previously unseen design scalability with competitive performance over the existing FPGA and ASIC encoder implementations.

Joint Source-Channel Decoding of Polar Codes for HEVC-Based Video Streaming

Ultra High-Definition (UHD) and Virtual Reality (VR) video streaming over 5G networks are emerging, in which High-Efficiency Video Coding (HEVC) is used as source coding to compress videos more efficiently and polar code is used as channel coding to transmit bitstream reliably over an error-prone channel. In this article, a novel Joint Source-Channel Decoding (JSCD) of polar codes for HEVC-based video streaming is presented to improve the streaming reliability and visual quality. Firstly, a Kernel Density Estimation (KDE) fitting approach is proposed to estimate the positions of error channel decoded bits. Secondly, a modified polar decoder called R-SCFlip is designed to improve the channel decoding accuracy. Finally, to combine the KDE estimator and the R-SCFlip decoder together, the JSCD scheme is implemented in an iterative process. Extensive experimental results reveal that, compared to the conventional methods without JSCD, the error data-frame correction ratios are increased. Averagely, 1.07% and 1.11% Frame Error Ratio (FER) improvements have been achieved for Additive White Gaussian Noise (AWGN) and Rayleigh fading channels, respectively. Meanwhile, the qualities of the recovered videos are significantly improved. For the 2D videos, the average Peak Signal-to-Noise Ratio (PSNR) and Structural SIMilarity (SSIM) gains reach 14% and 34%, respectively. For the 360֯ videos, the average improvements in terms of Weighted-to-Spherically-uniform PSNR (WS-PSNR) and Voronoi-based Video Multimethod Assessment Fusion (VI-VMAF) reach 21% and 7%, respectively.

Perceptual Quality Assessment of HEVC and VVC Standards for 8K Video

With the growing data consumption of emerging video applications and users&#x2019; requirement for higher resolutions, up to 8K, a huge effort has been made in video compression technologies. Recently, versatile video coding (VVC) has been standardized by the moving picture expert group (MPEG), providing a significant improvement in compression performance over its predecessor high efficiency video coding (HEVC). In this paper, we provide a comparative subjective quality evaluation between VVC and HEVC standards for 8K resolution videos. In addition, we evaluate the perceived quality improvement offered by 8K over UHD 4K resolution. The compression performance of both VVC and HEVC standards has been conducted in random access (RA) coding configuration, using their respective reference software, VVC test model (VTM-11) and HEVC test model (HM-16.20). Objective measurements, using PSNR, MS-SSIM and VMAF metrics have shown that the bitrate gains offered by VVC over HEVC for 8K video content are around 31&#x0025;, 26&#x0025; and 35&#x0025;, respectively. Subjectively, VVC offers an average of around 41&#x0025; of bitrate reduction over HEVC for the same visual quality. A compression gain of 50&#x0025; has been reached for some tested video sequences regarding a Student&#x2019;s t-test analysis. In addition, for most tested scenes, a significant visual difference between uncompressed 4K and 8K has been noticed.